Pham, Hoang Nhat

Multimodality imaging plays a pivotal role in ventricular tachycardia (VT) ablation by providing critical insights into arrhythmogenic substrates and guiding procedural strategies. This updated review explores the integration of various imaging techniques, including echocardiography, cardiac magnetic resonance (CMR), multidetector computed tomography (MDCT), electroanatomical mapping (EAM), and nuclear imaging, to optimize VT ablation outcomes. Echocardiography, particularly transthoracic echocardiography (TTE), is an essential first-line tool for evaluating structural heart disease and left ventricular function. Moreover, echocardiography aids in risk stratification and procedural planning by detecting regional wall motion abnormalities and thrombus formation. Meanwhile, intracardiac echocardiography (ICE) enhances ablation precision by providing real-time catheter visualization, improving procedural success, and reducing complications such as cardiac tamponade. Nonetheless, CMR is the gold standard for myocardial tissue characterization, enabling the identification of scar burden and conduction channels critical for VT pathogenesis. Late gadolinium enhancement (LGE) facilitates preprocedural planning by localizing arrhythmogenic substrates, predicting VT recurrence risk, and informing ablation strategies. Additionally, T1- and T2-mapping techniques refine the assessment of myocardial fibrosis and inflammation, further improving patient selection and outcomes. MDCT complements CMR by offering high-resolution anatomical visualization and aids in delineating scar distribution, epicardial fat, and vascular structures, informing safe and effective ablation approaches. The integration of these imaging modalities significantly enhances VT ablation precision, reduces recurrence rates, and improves patient outcomes.

This cross-sectional study investigates the association between lipoprotein(a) levels and risk of ventricular arrhythmias among patients with heart failure with reduced ejection fraction receiving implantable cardioverter-defibrillator therapy.

Background: The timing of coronary artery bypass grafting (CABG) in patients with non-ST-elevation myocardial infarction (NSTEMI) may critically impact clinical outcomes, yet the ideal surgical window remains unclear. We aimed to evaluate the association between time-to-CABG and in-hospital outcomes among NSTEMI admissions undergoing CABG. Methods: This retrospective cohort study utilized the US National Inpatient Sample database from 2017 to 2021 to evaluate the association between time-to-CABG and key in-hospital outcomes, including mortality, cardiac arrest, cardiogenic shock, ischemic stroke, acute kidney injury, and blood transfusion rates, while assessing length of stay (LOS) and hospital charges exclusively among survivors. Adult admissions with principal diagnosis of NSTEMI who underwent CABG without prior interhospital transfer were grouped by the calendar day of CABG from admission (0, 1, 2, 3, 4, 5, 6, and ≥7). Multivariate regression models were used to assess the outcomes across these eight groups. Results: Of 142,200 included admissions, same-day CABG (hospital day 0) was associated with the highest rates of in-hospital mortality, cardiac arrest, cardiogenic shock, and ischemic stroke. The adjusted odds of mortality, cardiac arrest, and cardiogenic shock were lower among admissions undergoing CABG between days 2 and 5. Likewise, the adjusted odds of ischemic stroke were lowest when CABG occurred on days 2 to 4. The odds of AKI increased when CABG was delayed beyond day 6, whereas blood transfusion rates showed no statistically significant association with time-to-CABG. Among survivors, LOS and hospital charges progressively increased with delayed CABGs. Conclusions: Among NSTEMI admissions undergoing CABG, CABG performed on hospital days 2 to 4 was associated with lower adjusted odds of several adverse in-hospital outcomes compared with same-day CABG. Further prospective studies are needed to validate these results and guide clinical decision-making.

Background: Disparities exist in the representation of genders in cardiovascular clinical trials. Atrial fibrillation (AF) is associated with significant morbidity and mortality; however, understanding regarding the representation of women in AF-related clinical trials remains limited. Therefore, this systematic review sought to evaluate the representation of women in AF-related clinical trials. Methods: We conducted a systematic review of clinical trials using the PubMed, Scopus, and EMBASE databases from 1996 to January 1st, 2024, focusing on AF-related lifestyle interventions, pharmacological treatments, catheter ablation, and device therapies for AF. Data extraction and analysis encompassed trial characteristics, participant demographics, and funding sources. The primary outcome was the prevalence of female enrollees, quantified through participation-to-prevalence ratios (PPRs). This was estimated overall and stratified by funding source, intervention type, and enrollment region. Results: Of the 103 clinical trials involving 218,322 participants (39.5% female), the PPR ranged from 0.00 to 1.73, with an average PPR of 1.03. Meanwhile, 43% of the trials exhibited female under-representation (PPR, <0.8). University-funded trials showed higher female enrollment (mean PPR, 0.951) compared to industry/government-funded trials (mean PPR, 0.800). No differences were observed in the representation of women when comparing enrollment regions or intervention types. Conclusions: Despite advancements in AF management, gender disparities persist in AF-related clinical trial representation, particularly in industry/government-funded studies compared to university-funded trials. Thus, addressing implicit biases and enforcing sex equality guidelines are critical steps toward more inclusive cardiovascular research.

Background. Liver transplant recipients face high risks of cardiometabolic events after transplant, driven by posttransplant weight gain, diabetes, hypertension, as well as immunosuppression-related side effects. Glucagon-like peptide-1 receptor agonists (GLP1RAs) improve metabolic and cardiorenal outcomes in nontransplant populations, but their role in liver transplant recipients remains understudied. Methods. This retrospective cohort study used TriNetX data (January 2010–December 2023) to compare outcomes in liver transplant recipients prescribed GLP1RAs (semaglutide, dulaglutide, liraglutide) within 1-mo posttransplant (n = 546) versus nonusers (n = 37 153). Propensity score matching (1:1) balanced demographics, comorbidities, and medications (n = 541 per group). Outcomes included mortality, hospitalizations, cardiovascular/renal/respiratory events, and graft outcomes. Results. Over a mean follow-up 838.5 d (SD 291.9) in the GLP1RA cohort and 884.3 d (SD 313.7) in the non-GLP1RA group, GLP1RA use was associated with a 43% lower all-cause mortality (7.0% versus 12.9%; hazard ratio [HR], 0.566; 95% confidence interval [CI], 0.381-0.841) and 39% fewer hospitalizations (60.4% versus 74.5%; HR, 0.613; 95% CI, 0.530-0.710). Acute heart failure (HR, 0.386; 95% CI, 0.285-0.524), renal failure/dialysis (HR, 0.489; 95% CI, 0.413-0.579), and respiratory failure (HR, 0.484; 95% CI, 354-0.662) risks were significantly reduced. No differences were observed in graft failure/rejection, myocardial infarction, stroke, atrial fibrillation/flutter, ventricular tachycardia, or ischemic optic neuropathy. Conclusions. Early GLP1RA initiation in liver transplant recipients was associated with reduced mortality, hospitalizations, respiratory, and cardiorenal complications without compromising graft safety. These findings support GLP1RAs as a promising adjunct therapy, warranting prospective trials to confirm benefits in this high-risk population.

aims: We assessed the diagnostic accuracy of the SVEAT score in predicting 30-day major adverse cardiac events (MACE) in comparison with the well-established HEART and TIMI scores. background: Acute chest pain (ACP) is a common symptom in emergency departments. Various risk stratification tools have been developed to assess patients presenting with ACP. The Simple Vascular Event Assessment Tool (SVEAT) is the most recent scoring system introduced, based on five variables: Symptoms of chest pain, history of Vascular disease, ECG, Age, and Troponin-I. objective: We assessed the diagnostic accuracy of the SVEAT score in predicting 30-day major adverse cardiac events (MACE) in comparison with the well-established HEART and TIMI scores. method: Following PRISMA guidelines, a systematic literature search was conducted across five databases until June 22, 2024. Four studies comprising 1,520 patients were included in this meta-analysis. The predictive accuracy of the SVEAT, HEART, and TIMI scores for 30-day MACE was assessed by the area under the receiver operating characteristic curve (AUC). Heterogeneity was evaluated using the I² statistic, with values over 75% indicating significant heterogeneity. Indirect comparisons among the scores were performed using the Z-test. result: Pooled AUC for the SVEAT score was 0.92 (95% CI: 0.86-0.98), indicating superior predictive accuracy compared to the HEART (AUC: 0.86, 95% CI: 0.81-0.92) and TIMI (AUC: 0.82, 95% CI: 0.69-0.96) scores. However, significant heterogeneity (I² = 90.6%) was observed across studies, potentially due to variations in patient demographics, clinical settings, and outcome definitions. Despite the higher AUC, indirect Z-test comparisons revealed no statistically significant differences between the scoring systems. conclusion: SVEAT score demonstrates potential as an accurate tool for predicting 30-day MACE in patients with ACP. other: N/A

This cohort study examines the association of bruton tyrosine kinase inhibitor therapy in B-cell malignant disease with increased risk of pericardial effusion and cardiovascular outcomes.

ABSTRACT Background Prolonged QT interval is common in end‐stage renal disease (ESRD) on dialysis, but its long‐term cardiovascular (CV) implications remain unclear. Methods Using TriNetX network (2010–2024), we identified adults with ESRD on dialysis and categorized them by QTc status. After 1:1 propensity score matching ( n = 3428/group), outcomes (hazard ratio [HR]) were assessed using Cox regression. Results Prolonged QTc (> 500 ms) was associated with higher risk of all‐cause mortality (HR 1.67; p < 0.001), MACEs (HR 1.40; p < 0.001), cardiac arrest (HR 1.75; p < 0.001), sustained ventricular arrhythmia (HR 1.66; p < 0.001), new‐onset atrial fibrillation (HR 1.12; p = 0.01), and acute myocardial infarction (HR 2.19; p < 0.001). Conclusions In ESRD patients on dialysis, prolonged QT interval was independently associated with adverse CV outcomes and mortality.

Coronary artery disease (CAD) remains the leading cause of cardiovascular morbidity and mortality worldwide, with plaque composition and morphology being as key determinants of disease progression and clinical outcomes. Accurate plaque characterization is essential for risk stratification and therapeutic decision-making, yet conventional image interpretation is limited by inter-observer variability and time-intensive workflows. Artificial intelligence (AI) models have emerged as a transformative tool for automated coronary plaque analysis across multiple imaging modalities. AI-driven models demonstrate high diagnostic accuracy for plaque detection, segmentation, quantification, and vulnerability assessment. Integration of AI-derived imaging biomarkers with clinical risk scores can further enhance prediction of major adverse cardiovascular events and supports personalized management. These advances position AI-enhanced imaging as a powerful adjunct for both invasive and non-invasive evaluation of CAD. Despite its promise, important barriers to widespread clinical adoption remain, including data heterogeneity, algorithmic bias, limited model transparency, insufficient prospective validation, regulatory challenges, and incomplete integration into clinical workflows. Addressing these challenges will be essential to ensure safe, generalizable, and cost-effective implementation of AI in routine cardiovascular care.